Senior AI Machine Learning Engineer
The Hartford4 months ago
Remote, WorldwideSenior
Base Salary
$117k - $176k/yr
Responsibilities
- Research, experiment with, and implement generative AI and machine learning algorithms, tools, and technologies.
- Design, develop, maintain, deploy, and monitor production-grade machine learning solutions and Models as a Service.
- Build repeatable architectural patterns, cloud-based web services, data pipelines, CI/CD pipelines, and infrastructure-as-code solutions.
- Deliver model deployment milestones in AWS and GCP and promote MLOps best practices.
- Collaborate with enterprise data, data science, business, cloud enablement, enterprise architecture, product, engineering, and operations partners.
- Mentor junior engineers and peers, provide technical thought leadership, and present new concepts to technical audiences.
- Assess new data sources, analytical techniques, and technologies to identify business opportunities and competitive advantage.
Requirements
- A master’s degree in a related field or 5+ years of equivalent experience in a research or DevOps function.
- At least 4 years of ML engineering, data manipulation, and application development experience.
- At least 4 years of Python development experience and at least 4 years working with infrastructure as code and CI/CD pipelines.
- At least 1 year of insurance or broader financial services experience and at least 1 year of SQL development experience.
- Development experience with both AWS and GCP, including familiarity with SageMaker and Streamlit.
- Experience building and deploying cloud-based web services, CI/CD pipelines, infrastructure-as-code solutions, and end-to-end model development lifecycles.
- Expert-level GitHub experience, including GitHub Actions, and strong object-oriented development experience using Python, Java, or C#.
- Familiarity with big data technologies, relational database platforms, workflow automation, data pipeline architecture, web security, credentials, and API management.
- Experience with Docker, Kubernetes, EC2, ML and data pipeline orchestration services, and ML frameworks such as TensorFlow, Anaconda, and scikit-learn.
- Strong data structures and algorithms knowledge, solution design and architecture experience, and familiarity with generative AI, agentic workflows, and embedding LLMs into automated processes.
- Must be authorized to work in the United States now and in the future without company sponsorship.
Benefits
- Hybrid schedule requiring work in a company office three days per week, Tuesday through Thursday.
- Office locations include Columbus, Ohio; Chicago, Illinois; Hartford, Connecticut; and Charlotte, North Carolina.
- The total compensation package may include short-term or annual bonuses, long-term incentives, and on-the-spot recognition.
- The company will not support the STEM OPT I-983 Training Plan endorsement for this position.